Modelling an off-grid integrated renewable energy system
electrification in India using photovoltaics and anaerobic digestion
for
rural
Castellanos, J. Ga, * Walker, M.a, Poggio, D.a, Pourkashanian, M.a and Nimmo, W a.,
* Corresponding author. E-mail: w.nimmo@leeds.ac.uk, tel: +44113 3432513
a
Energy Technology Innovation Initiative (ETII), Faculty of Engineering, University of
Leeds, Leeds, UK, LS2 9JT
Abstract
This work describes the design optimisation and techno-economic analysis of an offgrid Integrated Renewable Energy System (IRES) designed to meet the electrical
demand of a rural village location in West Bengal – India with an overall electrical
requirement equivalent to 22 MWh year-1. The investigation involved the modelling of
seven scenarios, each containing a different combination of electricity generation
(anaerobic digestion with biogas combined heat and power (CHP) and photovoltaics)
and storage elements (Vanadium redox batteries, water electrolyser and hydrogen
storage with fuel cell). Microgrid modelling software HOMER, was combined with
additional modelling of anaerobic digestion, to scale each component in each
scenario considering the systems' ability to give a good quality electricity supply to a
rural community. The integrated system which contained all of the possible elements
- except hydrogen production and storage presented the lowest capital ($US 71k)
and energy cost ($US 0.289 kWh-1) compared to the scenarios with a single energy
source. The biogas CHP was able to meet the electrical load peaks and variations
and produced 61% of the total electricity in the optimised system, while the
photovoltaics met the daytime load and allowed the charging of the battery which
was subsequently used to meet base load at night.
Keywords
Integrated renewable energy system, micro-grid, photovoltaic, anaerobic digestion,
hydrogen fuel cell, rural electrification.
Nomenclature
a
Specific biogas production [m3 kg-1 VS]
A
Total surface area of the anaerobic digester area [m2]
B
Annual biogas usage [m3 year-1]
C
Specific heat of the feedstock [kJ kg-1 ⁰C-1]
Ci
Influent Volatile Solids (VS) content [kg VS kg-1 Wet weight]
HL
Heat loss of the anaerobic digester [kW]
HF
Influent feedstock heating to the operating temperature [kW]
HT
Total thermal load of the anaerobic digester [kW]
OLR Organic loading rate of the anaerobic digester [kg VS m-3 day-1]
Q
Volumetric flow rate of feedstock [m3 day-1]
q
Volumetric flow rate of feedstock [m3 s-1]
Ta
Ambient temperature [⁰C]
Top
operating temperature of the anaerobic digester [⁰C]
1
U
Vr
ρ
Total heat transfer coefficient [kW m-2 ˚C-1]
Anaerobic digester working volume [m3]
Feedstock density [kg m-3]
Abbreviations
AD
Anaerobic Digestion
BURD
Bridging the Urban-Rural Divide
CHP
Combined Heat and Power
COE
Cost of Electricity
DC-AC
Direct current to Alternating Current Converter
IRES
Integrated Renewable Energy System
LOLP
Loss of Load Probability
LPG
Liquid Petroleum Gas
NPC
Net Present Cost
O&M
Operation and Maintenance
PV
Photovoltaic
VRB
Vanadium Redox Battery
1. Introduction
India has shown an accelerated economic growth, however like other developing
countries most of its population (~70%) live in remote rural areas which are not
connected to the national electrical grid. These villages and communities either have
an insufficient electricity supply or do not have it at all [1]. Whereas the affluent
sector are benefiting from the economic expansion of India, remote, rural
communities are being excluded. A recent investigation claimed that an extension of
the Indian national grid in order to electrify rural communities is not feasible [2]. With
119,560 sites that are not electrified, due to their remote location, it is economically
unfeasible to connect 18,000 villages to the national electric grid. On average, these
villages require small power units with a capacity between 10-250 kW [2]. Taele et al.
claimed that due to the lack of public electricity in rural Africa, people are forced to
improvise domestic energy systems commonly based on kerosene or small diesel
engines [3] which suffer from frequent breakdowns, unsafe electrical and fuel storage
conditions, ad-hoc unreliable connections and high power losses.
For these reasons there is an increased interest in installing small scale renewable
generation systems to electrify these communities. However, due to the intermittence
in energy generation of many renewable systems depending on one single source,
this option may be unreliable. To increase the reliability of the renewable energy
system, the most suitable method is to develop Integrated Renewable Energy
Systems (IRES) which rely on multiple generation technologies.
Kanase-Patil et al. indicated that in some IRES configurations the conversion and
reconversion of energy by the battery units decrease the system’s efficiency and
increases the energy cost [4]. Alzola et al. claimed that the high cost of photovoltaic
(PV) panels is the main barrier for the extensive use of stand-alone systems [5]. An
2
investigation performed in Cameroon (average solar radiation 5.55 kWh m 2 day-1)
where a PV system (18 kW) was coupled with an Liquid Petroleum Gas (LPG)
generator (15 kW), found that the electricity cost for remote sites would be quite high
($1 0.720 kWh-1). Nandi et al showed that PV and battery ($ 0.621 kWh-1) power
systems are not as efficient as wind, PV and battery systems ($ 0.439 kWh-1); it was
also illustrated that energy systems with a big PV generator required large battery
storage systems and thus greater investment and eventually higher energy cost [6].
This finding suggests that well managed integrated renewable energy systems,
which combine a higher number of technologies, potentially produce cheaper energy
than simple energy systems [7].
The objective of this project was to assess the design and optimisation of a hybrid
renewable system for providing electricity to a rural location in West Bengal, India.
The techno-economic performance of seven scenarios, based on combinations of
different technologies, was explored.
2 Materials and Methods
Given the abundance of sunlight and biomass available in the research area (India),
the chosen energy conversion technologies were PV and anaerobic digestion (AD),
with a Combine Heat and Power (CHP) generator fuelled by biogas. CHP systems
based on both reciprocating engines and microturbines were considered and
scenarios were based on combinations of these along with two storage technologies:
vanadium redox batteries (VRB), and the combination of a water electrolyser and
hydrogen storage with fuel cell for electricity production. A third storage option, zinc
bromide batteries, was also briefly assessed. In order to determine a final optimal
IRES configuration, the various technologies mentioned above were combined with
each other. Figure 1 portrays the general concept of the IRES proposal for a typical
rural village.
2.1 Load Profile
This research forms part of the Bridging the Urban Rural Divide (BURD) joint
India/UK project and as part of this work a load profile was created that represents
the electrical demand of a village in West Bengal containing around 1000 residents
who currently have no direct access to electricity [8]. This is shown in figure 2. The
demand is split into various categories and includes economic activity i.e. grinding
spices, water pumping, the operation of a medical centre, adult and child education
facilities, lighting and entertainment. The overall electrical load is equivalent to 22
MWh/year. The error bars denote a 60% possible variation which is the expected
maximum daily variation during each hourly period.
2.2 Microgrid system modelling - HOMER
Micro-grid modelling was performed using HOMER. This software allows simulation
of the performance of an energy system with uncertain operational conditions,
allowing robust design with reduced project capital risk. A large number of
permutations of the overall system were created with varying capacity (storage,
power output) of each component. Each of these permutations was tested to assess
whether it could meet the load requirement. The HOMER package was then used to
1
$ throughout this work refers to $US
3
list the permutations of the systems that can meet the demand and reports various
economic indicators upon which the optimal scenario could be chosen.
2.2.1 Scenarios considered
The scenarios that were explored are shown in Table 1. Scenarios A and B use PV
as the primary energy generator with differing storage technologies. Scenarios C-F
use AD and a biogas CHP as the primary energy generation, with differing
generation technologies and capacities of the CHP used. For each CHP technology
two scenarios were explored; one with a high and low capacity engine and one with
two similarly sized engines. Note that this approach was chosen since initial results
with only a single CHP showed large amounts of wasted energy since the CHP
needed to be scaled according to the peak demand which is much higher than the
base load. Finally, scenario G, the fully integrated energy system, was designed
based on the better ranked technologies from the previous modelling.
2.2.2 Photovoltaic
The solar radiation is calculated by HOMER based on the hypothetical location of the
project site within West Bengal, India (latitude 23⁰ 16’ north and longitude 87⁰ 15’
east) which has a scaled daily average radiation of 4.826 kWh m -2 day-1 which
includes both direct and diffuse sources and measured on a horizontal surface. Table
2 shows the detail of the solar resource considered in this study. A derating factor
equivalent to 80% and ground reflectance of 20% were assumed. The 20 years
lifetime PV panels were considered not to have a tracking device, thus the angle at
which the panels are mounted relative to the horizontal was set at 23⁰. 16 sizes were
considered, distributed between 7 and 50 kW output capacity.
2.2.3 Vanadium redox battery
VRB was selected as the storage element in the PV system, as small sizes
appropriate to this system are commercially available. A cell stack with a lifetime
equivalent to 15 years was analysed, 8 different sizes of cell stack were considered
between 5 and 15 kW. The electrolyte lifetime is much longer (125 years). 9 sizes
were considered in the analysis, between 80 and 250 kWh. An overall round trip
efficiency of 80% was used. This data was provided in HOMER by Prudent Energy
VRB ® Systems (MD, USA) and further supported by personal communication with
Golden Energy Fuel Cell Co., Ltd. (China, Beijing).
2.2.4 Hydrogen storage system
The fuel cell system consisted of three elements: fuel cell, electrolyser and hydrogen
tank. The fuel cell operating lifetime was considered to be 40,000 hours. The
hydrogen consumption was fixed at 0.06 kg hour-1 kW -1. Four output capacities were
analysed between 8 and 15 kW. In the case of the electrolyser with a lifetime of 15
years and an efficiency of 85%, four different sizes were considered between 10 and
15 kW. Regarding the hydrogen tank the following hydride storage conditions were
assumed: pressure 10 bar, density 0.02 kg l-1 and storage efficiency equivalent to
90%. This data was provided in HOMER by Hydrogen Bank Technology Inc. (New
Taipei City, Taiwan) and supplemented with additional data from [9, 10]. Various
hydrogen tank capacities with a lifetime of 25 years were included in the optimisation
analysis with 9 capacities between 15 and 60 kg.
4
2.2.5 Generators
The expected operating lifetime of the CHP generators was 60,000 hours and their
operation schedule was assumed to be fixed and manually programmed. To cover
the load peaks, the high capacity generators operated between 12pm – 2pm and
6pm – 10pm; seven sizes were considered between 8 and 15 kW. To cover base
load, the low capacity generators operated between 12am – 12pm, 2pm – 6pm, and
10pm – 12am; four sizes were considered between 2 and 5 kW. In the similar
capacity generator scenarios, one generator would operate continuously, while the
other one would only operate during peak times (i.e. 12pm – 2pm and 6pm – 10pm).
6 sizes were considered for similar capacity generators between 3 and 8 kW.
Microturbines were evaluated considering a minimum part-load of 60%, heat
recovery efficiency of 45%, biogas consumption of 0.25 m3 hour-1 kW-1 output and an
intercept coefficient of 0.2 m3 hour-1 kW-1 rated. Reciprocating engines were
evaluated considering a minimum part-load of 30%, heat recovery efficiency of 60%,
biogas consumption of 0.4 m3 hour-1 kW -1 output and an intercept coefficient of 0.267
m3 hour-1 kW -1 rated. All CHP data was obtained from references [9-12]. This
combined data gave overall efficiency vs. load curves as shown in figure 3.
2.2.6 Economic and financial variables
Capital and O&M costs of the main components of the IRES are shown in table 3
including the sources of data.
Operation and maintenance (O&M) for PV and AD was assumed to be cost free due
to the highly robust nature of both of these systems, and in addition that the routine
activities have very low time requirements and do not require a skilled workforce.
These activities would consist of the cleaning of the PV modules surface, vegetation
management, wildlife prevention, the collection of the AD feedstock, the
feeding/discharging operations of the digester and in addition none-routine
operations such as degritting, removing blockages and minor repairs etc. It has been
assumed that the rural community would freely cooperate with these O&M activities
in order to minimize the cost of energy. Also the AD feedstock was considered to be
cost free as will be discussed in section 2.3. Note that the O&M cost of the
generators was considered separately from the AD system as shown in table 3.
Regarding the O&M cost of the hydrogen tank and electrolyser, due to the complexity
of certain hydrogen equipment, this O&M cost of hydrogen equipment is generally
included in the initial capital cost, this means that private companies generally offer
leasing purchase contracts where the supplier is committed with the periodical
maintenance of the equipment.
An annual real interest of 6% over a period of 20 years (i.e. life time of this energy
project) was used in the calculation of economic indicators.
2.3 Additional Modelling – Anaerobic Digestion
The anaerobic digester was modelled outside of HOMER. Based on the feedstock
biomass properties this tool was applied to determine the volume of the digester,
feedstock requirement for its operation and the implications of the AD unit within the
economic variables of each scenario. The feedstock requirement (Q) was calculated
based on the composition and biogas potential of water hyacinth. This biomass
source was chosen since it, and other similar aquatic weeds, are prevalent in West
5
Bengal and in other tropical parts of the world and in many cases represents an
invasive species which is a nuisance since it rapidly spreads in watercourses [13].
Therefore not only can aquatic weeds be considered a free biomass resource (a
waste stream) but also that in some cases it’s clearing from local watercourses would
be performed periodically anyway. Water hyacinth can easily be cultivated in these
areas to provide a reliable feedstock source to the anaerobic digester. The
characteristics the input biomass were as reported by Chanakya et al [13]: 10% of
total solids, 85% of volatile solids (VS) (therefore Ci = 0.085 kg VS kg-1 wet weight),
with a specific biogas production equivalent to 0.35m 3 kg-1 VS. The specific heat was
assumed to be equivalent to that of water 4.18 kJ kg-1 ⁰C-1 and the feedstock density
was set at 1040 kg m-3.
The output for each scenario from HOMER was the annual biogas requirement to
supply the CHP generator. Since anaerobic digesters work best when operated in a
steady state the biogas production was assumed to be constant throughout the year,
with the daily difference between biogas supply and demand met using a low
pressure storage gasometer. The necessary daily feedstock requirement was then
calculated by applying equation 1.
Q = B / (365 ρ a Ci)
[m3 day-1]
(Eq. 1)
The working volume of the anaerobic digester was calculated using equation 2.
Vr = (Q Ci) / (ρ OLR)
[m3]
(Eq. 2)
A headspace of 10% of the working volume was added to obtain the total volume of
the digester which was assumed to be a cylindrical tank of aspect ratio 1 (height =
diameter) to minimise the surface area and therefore heat loss. Thus the surface
area could be calculated.
To calculate the thermal demand of the digester a daily temperature profile was
created for each month using seasonal data from the India Meteorological
Department [14] supplemented with daily variation obtained from Time and Date
Aksjeselskap (Stavanger, Norway). Digester hourly heat losses were calculated
based on a continuously stirred tank reactor (CSTR) with structural properties as
shown in table 4. The thermal load of the digester was calculated using equation 3,
and consisted of the heat loss/gain through the insulated tank, and the heat required
heat the incoming feedstock to the operating temperature. These were calculated on
an hourly basis using equations 4 and 5.
HT = HL + HF
[kW]
(Eq. 3)
HL = U A (Ta – Top)
[kW]
(Eq. 4)
HF = C q ρ (Ta – Top)
[kW]
(Eq. 5)
The operating temperature of the digester was a design variable. It was found in
initial simulations that operation at mesophilic (37˚C) or thermophilic (55-65 ˚C)
temperature led to a large heat load which could not be met using only the waste
heat from the CHP. This resulted in additional biogas demand to feed a boiler (as
shown in figure 1) to produce the required heat. It was found that given the
temperature profile in West Bengal, an operating temperature equivalent to 30⁰C
would reduce the AD heat losses, whilst still allowing a stable anaerobic process.
6
However, such an operating temperature would place a lower limit on the organic
loading rate of the digester which was set at 2 kg VS m -3 day-1 ,as suggested by Kiely
[15]. Given all of the design constraints above, and the feedstock properties as per
[13], the digester was effectively modelled as a conventional mixed tank digester with
hydraulic retention time of 42.5 days, a daily volumetric biogas production of 0.7
(m3biogas m-3working volume).
3. Results and Discussion
3.1 Energy Systems Depending on a Single Source
3.1.1 Photovoltaic Scenarios
Table 5 shows the outputs from HOMER, representing the most suitable scaling of
each of the system components, firstly, based on their ability to meet the load
demand with a Loss of Load Probability (LOLP) of 1% and secondly, based on the
lowest Net Present Cost (NPC) and Cost of Electricity (COE), which is calculated
based on the economic variables of each scenario. It can be seen that the capacity
of the system components for scenarios A and B are relatively large with respect to
the maximum load on the system (12.5kW). This is a consequence of the use of PV
technology as the energy generating unit. The system not only needs to satisfy the
energy demand during the day but also to secure enough energy generation and its
storage so there is sufficient stored energy to allow a quality supply during the night
and during periods of cloudy conditions. The low LOLP requirement also led to an
over dimensioning of the system in these scenarios which could be reduced by
increasing the LOLP. However, this would lead to a reduction in the quality of the
supply which may be unacceptable to the users who expect energy on demand. The
large generation capacities led to high proportions of wasted electrical energy for
both scenarios: this occurs when the storage element of the system (VRB or
Hydrogen tank) is full and there is no use for the electrical energy produced by the
PV during the daytime on days with high solar radiation levels. Such a big amount of
wasted energy can be harnessed by including an intelligent battery inverter control
unit (e.g. SMA Sunny Island System) so that, whenever there is no energy demand
and the batteries are fully charged, the system automatically delivers the energy to
secondary energy needs e.g. water pumping for irrigation purposes.
Initially, a third PV based scenario was considered in combination with zinc bromide
batteries. However, after researching the availability of these types of battery, this
scenario was disregarded because the minimum manufactured capacity is 25 kW
[16, 17]: as a consequence the system would have been over-dimensioned and
uneconomical.
Scenario B, which used hydrogen storage, resulted in bigger capacity of the installed
PV and higher cost of energy than Scenario A, which used batteries for energy
storage. It is important to take into account that in contrast to a battery backup which
consists of a single unit with an overall efficiency of 75 – 80%, a hydrogen backup
system consists of three elements: fuel cell, electrolyser and H 2 tank. Where the
overall efficiency of a fuel cell coupled with an electrolyser unit is 25 – 60%, an H2
tank efficiency is between 80 – 90% [18]. Although these efficiencies may be seen as
high for individual energy equipment, these three elements together represent an
overall round-trip efficiency of the hydrogen storage system of approximately 50%.
Therefore the PV capacity must substantially exceed the expected electric load.
7
According to the results illustrated up to this point, although Scenario B represents
an innovative and promising storage solution, it is still in early development, thus,
appears that the most feasible PV energy system is Scenario A where a PV is
coupled with a VRB unit.
3.1.2 Anaerobic Digestion scenarios
The results from the AD scenarios are summarised in table 6. The decision to use a
combination of two separate CHP units for each scenario was made after initial
simulations with a single CHP showed large proportion of excess electricity
generated (results not shown). This was caused by a combination of the restraints
imposed on the CHP in terms of minimum operating load (60% for microturbine and
30% for reciprocating engine) and the challenging demand profile, having a large
difference between base and peak load. Since these scenarios contained no energy
storage elements, the CHP was dimensioned such that it could satisfy the peak load
(12.5 kW) and therefore the minimum power output was 7.5 and 4.5 kW for
microturbine and reciprocating engines respectively which is much higher than the
base load (1 kW). Operation with two CHP units resulted in a smaller proportion of
electricity wastage. The excess electricity production of these scenarios could have
been improved by the addition of a battery since this would have acted as a buffer
between the supply and demand when the CHP would have otherwise been
operating with excess electrical output. However, in preliminary investigations this
type of system was found to be financially intensive (results not shown) due to the
requirement of AC-DC and DC-AC converters, the inefficiency of the repeated
electrical conversion, and in addition could have a negative impact on the CHP due
to a large number of daily stop-start cycles.
From results presented in table 6, it can be seen that the microturbine based
scenarios (C & D) resulted in a larger proportion of wasted electricity but a smaller
feedstock usage and anaerobic digester volume, when compared with reciprocating
engine scenarios (E & F). The increased wastage results from the inferior part load
performance of microturbine, which have a minimum working load at 60% of the
rated capacity); despite this disadvantage, the greater fuel efficiency in microturbines
resulted in lower overall feedstock use. Clearly, operating with one low and one high
capacity generator can reduce the excess energy generated since the lower capacity
unit can better supply the base load whereas, the higher capacity unit can be used
only during the peak load.
3.1.3 Economic comparison of photovoltaic and anaerobic digestion scenarios
Figure 4 illustrates the initial investment required for each scenario. Amongst the two
PV scenarios, Scenario A is the least capital intensive pathway at $ 97k while
Scenario B is the most expensive alternative at $ 234k. An additional analysis of the
disregarded scenario, PV coupled with ZBB, also was shown to be capital intensive $
143k. Indeed, VRB is a cheaper alternative than ZBB due to the fact that in the case
of the ZBB, its minimum energy storage capacity is 25 kWh.
These results suggest that coupling PV with a VRB provides flexibility to the system
where the energy system is not restricted to a minimum manufactured size of the
battery. Hence, the battery size can be easily adapted to the electrical load of a
particular application. Indeed, manufacturers such as Prudent Energy and Golden
Energy Fuel Cell Co., Ltd., some of the world leaders on research and manufacturing
8
of this particular flow battery storage, are targeting the market for off-grid rural
electrification and other similar applications such as off-grid telephone masts, and
therefore a 12 kW peak electrical load is suitable for using VRB. The capital and
O&M costs associated with scenario B are the highest of all of the options
considered. This is mostly due to the high costs of fuel cell technology.
The prediction that the NPC of scenarios C and D is lower than those using
reciprocating engines (E and F) is due to a combination of advantages offered by
microturbine technology at the investigated scale. The largest impact is the higher
overall efficiency of these engines and therefore the conclusion is highly sensitive to
the input data supplied from the literature and industry as per table 3. Microturbines
were found to have lower O&M costs which are because of their basic mechanical
layout and fewer moving parts than reciprocating engines [19, 20]. A typical
maintenance of a reciprocating engine involves inspection and replacement of
valves, pistons, gas and air filters, spark plugs, gaskets, rings and electronic
components. However, in India the O&M of reciprocating engines would be
performed locally using cheap labour and low-tech expertise, whereas the
microturbine would need to be returned to the manufacturer where it would be
serviced in a high-tech environment. This means that the two quoted O&M figures
may be skewed in favour of microturbines. Despite this, the greater mechanical
efficiency of the microturbine results in a smaller dimension of the CHP itself as well
as the anaerobic digester since less biogas is required to meet the electrical demand
which would still give lower capital and NPC even discounting the difference in O&M
cost.
Findings portrayed in this section were used to select the components used to
simulate the IRES in Scenario G. It was decided that this should be made from a
combination of Scenario A and C. Therefore, in order to increase the flexibility,
efficiency of the energy system, its reliability, offer a good and affordable quality of
electrical service and maximise the environmental value of the IRES, this fully
integrated system should involve PV, VRB, AD and a microturbine based CHP. For
maximum system efficiency the generation technologies need to be coordinated such
that the CHP is used only during peak load hours.
3.2 Performance of the Integrated Renewable Energy System
The performance of the various elements which interact within the IRES are shown in
Figure 5 and table 7 gives the details of the scale of the component systems. The
share of electricity generation is divided between the PV (39%, 4,394 hours year-1)
and the CHP microturbine (61%, 2,190 hours year-1). While the PV operates during
appropriate solar conditions to satisfy the base load during the day, the microturbine
is schedulable and is only used, during peak load times, i.e. between 12pm - 2pm
and 6pm – 10pm. At these times, the CHP can operate at full load and thus part load
efficiency losses are avoided and furthermore, during these times, the battery can be
recharged using the excess electricity. The microturbine operates at an average
electrical efficiency of 33.8%, which increases to 63.6%, if the thermal energy
recovery which is used to heat the digester is included. An important observation is
that, in this case, since the solar cells are not required to meet the peak electrical
demand, and are instead combined with a schedulable CHP, the relative sizing of the
PV and converter are a factor of four smaller than in scenario A despite them still
producing 39% of the total electricity supplied. Further to this, the AD plant is only
9
52% of the size of that in scenario B while the CHP produces 61% of the electricity
supply, the difference mainly being due to the fact that the CHP can be scheduled to
only be active during peak load periods leading to a lower excess electricity
production.
A typical day’s profile of load and electrical production of the IRES is shown in Figure
6. In this system only the excess electricity generated from the PV is stored in the
battery system and any excess biogas is not used. Hypothetically, any excess biogas
would be better used as a cooking fuel and/or stored in gasometers until it is
required. After 10pm when the energy load decreases, the electrical demand is
satisfied by the energy stored in the batteries. By operating the system in this semiautomatic way it was found that the overall efficiency of the IRES may increase along
with the life time and therefore the associated costs of the battery. Furthermore, and
similarly to what was stated previously, the IRES scenario results in only 4.5%
excess energy, lower than in either scenario A or C. However, it may still be worth
considering the use of an intelligent high-tech battery inverter control unit which
delivers the excess energy to secondary needs which could improve the quality of life
of the village inhabitants.
3.2.1 Economic Analysis of the Integrated Renewable Energy System
Although HOMER ranks the different systems according to its NPC, taking into
account that this research targeted, low income, rural location within developing
countries, the COE was determined as the most important economic feasibility
indicator of the project. Figure 8 illustrates the COE involved in each scenario. Note
that the capital cost of each of the scenarios has the largest impact on the effective
COE, where the COE is strongly influenced by the overall annualised cost and total
electrical supply presented by each scenario.
According to the above statement and results shown in Figure 8, Scenario G appears
as the most suitable pathway. Additionally, due to the fact that it does not simply
depend on one technology but on two energy generation technologies such as PV
and AD, the IRES could also have increased reliability. The capital cost of the IRES
is relatively lower than any other scenario which is due to the previously mentioned
synergy between the schedulable, non-schedulable and storage elements in this
integrated system. It is worth stressing that the scaling of the components in each
scenario is highly sensitive to the selected LOLP. The 1% LOLP which has been
used in this work represents a relatively high quality of supply in rural India and
before embarking on such a project it would be worth considering the required or
acceptable quality of supply since economic savings could be made in the case of a
higher LOLP. To attempt to quantify this, scenario G was simulated at additional
LOLP values of 2, 5, 10 and 20%, the results of which are shown in table 8. Whilst it
is true that reducing the desired quality of supply to a LOLP of 20% results in a
reduction in the capital cost and the installed generation capacity by 15% and 27%,
respectively, this benefit is not carried forward to the cost of the electricity over the
life of the project. The COE is only reduced by 2.1% due to less electricity being
supplied by the system despite a huge decrease in the supply quality. It is worth
mentioning that a benefit of increasing the allowed LOLP is that less excess
electricity is generated and therefore wasted, mainly because the PV system is not
over-dimensioned to meet unusual peaks in demand. Based on these results
depending on the required quality of supply the system may be designed with an
10
expected LOLP of 5% to give some reduction in capital cost, COE and excess
generation.
The electricity cost of the system proposed in this work of $ 0.289 kWh -1 is
comparable with other works in rural India e.g. 0.258 for a PV and battery system
[28], 0.24-0.47 for different configurations of PV, wind and batteries [29] and 0.216
for a PV, diesel and battery system [30](all in $ kWh-1). Furthermore a Greenpeace
study [21] found that the cost of electricity of microgrid systems based on biomass
(thermal) and PV in India was 0.304-0.384 $ kWh-1, and that this can be reduced to
0.176-0.208 $ kWh-1 if a local hydro power source is available. The report goes on to
explore the comparison between the cost of electricity from these isolated systems to
the extension of the electricity grid. While the cost of electricity for grid connected
customers is reported to be as low as 0.08 $ kWh-1, obviously much cheaper than
the cost from the IRES reported, once the costs of extending the grid are taken into
account the total cost can become greater for a distance as little as 5-13km.
A broader discussion of the benefits of the IRES would include the fact that AD offers
liquid and fibrous by-products which act as soil fertilisers and can improve crop yields
and soil conditions. This is a particular benefit to rural communities that otherwise
may not have the financial resources to add nutrients to their cultivated fields.
Therefore, they would improve the productivity within agriculture and livestock
sectors, or could even commercialise the fertilisers to neighbouring villages, thus,
increase their economic revenues.
Nonetheless, any scenario involving AD
represents a commitment to a work load demand from the community and there may
be local resistance to this aspect of the technology. AD not only provides biogas to
the microturbine, but this purpose is achieved by treating waste, hence, AD is a
sanitary remediation alternative. Therefore, in addition to the IRES low COE, this
scenario may represent a better option due to the fact that the IRES provides the
other benefits from AD.
4. Conclusions
The objective of this research was to investigate the electrification of a remote
community in West Bengal, India using an IRES. This research has involved the
selection of two PV, four AD and a combined AD & PV scenario using micro-grid
modelling software – HOMER. Each scenario was designed with the capability to
meet a specified electricity demand with daily variations for a full year. The design of
the various energy system scenarios was studied in terms of their techno-economic
performance to determine the most efficient path to follow while meeting the
electricity load of the rural community.
It was determined that the IRES containing PV, VRB, DC-AC converter, AD and a
microturbine CHP had many benefits compared with the other scenarios where only
one energy source was available. The IRES had a lower capital and electricity cost
over the life of the project was lower at $ 0.289 kWh-1 (c.f. $ 0.335-1.332 kWh-1 for
other scenarios) mainly due to the synergy between the various production and
storage elements at meeting the demanding load profile with a very high quality of
supply.
Rural electrification projects on developing countries such as this one based on the
electrical requirement of a typical community in West Bengal – India, not only
improve the quality of life of remote villages inhabitants but they also provide
11
business and research prospects for foreign and local engineering institutions. Such
institutions could offer the governments of developing countries technical
assessment, renewable energy technology supplies and installation services. Indeed,
this research has the potential to offer opportunities within several areas such as the
environment, technology, economic and social fields.
Acknowledgments
This research was funded by the Research Councils UK as part of the BURD joint
UK/India program.
12
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